RAPID: Daily Mobility Patterns and COVID-19 Risk among Urban Older Adults

RAPID：城市老年人的日常出行模式和 COVID-19 风险

• 批准号: 2029384
• 负责人: Kathleen Cagney
• 金额: $ 19.99万
• 依托单位: National Opinion Research Center
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-15 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029384&HistoricalAwards=false
• 关键词: RAPID; Daily; Mobility; Patterns; COVID

This project investigates the extent to which, among older adults, the ability to comply with public health guidelines is affected by demographic position and how this contributes to differences in exposure risk and health consequences. This study builds on an earlier study of activity patterns of a diverse sample of older adults to measure risk of spatial exposures prior to the pandemic and, through the collection of new waves of data, to measure spatial responses to the pandemic. The data from this project will inform future modeling of disease spread, providing more sophisticated assumptions regarding implementation and adherence to guidelines. The data also provide information that can be used to help decision makers develop and target interventions to minimize the emotional and physical health impacts of the pandemic on vulnerable populations.Building on three earlier waves of data collection in 2018 and 2019, three additional waves of data are collected during the pandemic. Respondents carry smartphones and answer several surveys a day providing location and other objective and subjective data concerning their activities. A brief telephone survey follows in 3-6 months. Analysis assesses effects of demographic and locational characteristics as well as change over time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目调查老年人遵守公共卫生准则的能力在多大程度上受到人口状况的影响，以及这如何导致暴露风险和健康后果的差异。这项研究建立在早期对不同老年人样本的活动模式研究的基础上，以衡量大流行前空间暴露的风险，并通过收集新一波数据来衡量对大流行的空间反应。来自该项目的数据将为未来的疾病传播建模提供信息，提供关于实施和遵守指南的更复杂的假设。这些数据还提供了信息，可用于帮助决策者制定干预措施，并有针对性地将疫情对弱势人群的情绪和身体健康影响降至最低。在2018年和2019年的前三波数据收集的基础上，在疫情期间又收集了三波数据。受访者携带智能手机，每天回答几项调查，提供地点和其他有关他们活动的客观和主观数据。3-6个月后会进行一次简短的电话调查。分析评估人口和地理特征的影响以及随时间的变化。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。